38 citations · 91 across the 4 of their papers we have counts for
4 papers
Jacobian Norm for Unsupervised Source-Free Domain Adaptation
Weikai Li, Meng Cao, Songcan Chen
Unsupervised Source (data) Free domain adaptation (USFDA) aims to transfer knowledge from a well-trained source model to a related but unlabeled target domain. In such a scenario,…
Partial Domain Adaptation without Domain Alignment
Weikai Li, Songcan Chen
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a well-labeled source domain to a different but related unlabeled target domain with identical label space. Cur…
Leave Zero Out: Towards a No-Cross-Validation Approach for Model Selection
Weikai Li, Chuanxing Geng, Songcan Chen
As the main workhorse for model selection, Cross Validation (CV) has achieved an empirical success due to its simplicity and intuitiveness. However, despite its ubiquitous role, CV…
Unsupervised Domain Adaptation with Progressive Adaptation of Subspaces
Weikai Li, Songcan Chen
Unsupervised Domain Adaptation (UDA) aims to classify unlabeled target domain by transferring knowledge from labeled source domain with domain shift. Most of the existing UDA metho…